This paper presents an asynchronous particle
filter algorithm for mobile robot position tracking, taking into account time considerations when integrating observations
being delayed or advanced from the prior estiamate time point. The interest of that filter lies in cooperative environments and
in fast vehicles. The paper studies the first case, where a sensor network shares perception data with running robots that receive accurate obeservations with large delays due to acquisition, processing and wireless communications. Promising simulated
results comparing a basic particle filter and the proposed one are shown. The paper also investigates a situation where a robot
is tracking its position, fusing only odometry and observations from a camera network partially covering the robot path.